Update README.md

README.md

@@ -171,35 +171,36 @@ For any licensing questions, contact us at ```[email protected]```
 **Prerequisites:**
 - **Install necessary libraries:**
 ```
-pip install transformers diffusers torch Pillow huggingface_hub
+pip install transformers diffusers torch Pillow huggingface_hub PIL io requests
 ```
 - **Code to Use the Model:**
 
 ```
-from transformers import AutoTokenizer, AutoModelForImageGeneration
-from diffusers import DiffusionPipeline
+from transformers import AutoTokenizer #, AutoModelForImageGeneration
+from diffusers import DiffusionPipeline, FluxPipeline
 import torch
 from PIL import Image
 import requests
 from io import BytesIO
 
 # Your Hugging Face API token
-API_TOKEN = "your_hugging_face_api_token"
+API_TOKEN = "<retacted>"
 
 # Load the model and tokenizer from Hugging Face
 model_name = "future-technologies/Floral-High-Dynamic-Range"
+#model_name = "black-forest-labs/FLUX.1-dev"
 
 # Error handling for model loading
 try:
-    model = AutoModelForImageGeneration.from_pretrained(model_name, use_auth_token=API_TOKEN)
-    tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=API_TOKEN)
+    #model = AutoModelForImageGeneration.from_pretrained(model_name, use_auth_token=API_TOKEN)
+    tokenizer = AutoTokenizer.from_pretrained(model_name, token=API_TOKEN)
 except Exception as e:
     print(f"Error loading model: {e}")
     exit()
 
 # Initialize the diffusion pipeline
 try:
-    pipe = FluxPipeline.from_pretrained(model_name, use_auth_token=API_TOKEN)
+    pipe = FluxPipeline.from_pretrained(model_name)
     pipe.to("cuda" if torch.cuda.is_available() else "cpu")
 except Exception as e:
     print(f"Error initializing pipeline: {e}")